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              <text>An efficient approach towards clustering using K-means algorithm</text>
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              <text>Distance measure; Elbow method; Gap-statistic method; Hopkins index; Partition clustering; Standard K-means process</text>
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              <text>Cluster analysis is one of the major knowledge mining methods in the field of data analytics; the approach used for clustering will influence the accuracy of the results and quality of the obtained clusters. A good clustering process or algorithm is one which increases the fit of the data points in each cluster and which satisfies the clustering criteria, if these measures are not met adequately the desired pattern will not be seen and the patterns obtained for analysis may turn out to be inaccurate or insufficient. This paper discusses the standard k-means clustering algorithm and provides an efficient approach towards clustering using the standard global K-means algorithm; the process eliminates the need for initializing random number of clusters multiple times which is followed as the standard process in the field. The effectiveness of the proposed approach was analyzed using the benchmark dataset and the implementation was performed using the well-known analytic tool R Studio and supporting packages.  IAEME Publication.</text>
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              <text>Aiyappa S.N.; Ramamurthy B.</text>
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              <text>International Journal of Civil Engineering and Technology, Vol-9, No. 2, pp. 705-714.</text>
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              <text>2018-01-01</text>
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              <text>&lt;a href="" target="_blank" rel="noreferrer noopener"&gt;&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042923571&amp;amp;partnerID=40&amp;amp;md5=f7d89e778c57439631dd5457aa75fade" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042923571&amp;amp;partnerID=40&amp;amp;md5=f7d89e778c57439631dd5457aa75fade&lt;/a&gt;</text>
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              <text>Restricted Access</text>
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              <text>ISSN: 9766308</text>
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              <text>Aiyappa S.N., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; Ramamurthy B., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India</text>
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